Pub Date : 2023-01-03DOI: 10.4108/eetsis.v10i3.2057
J. Arora, M. Tushir, Shivank Kumar Dadhwal
Possibilistic fuzzy c-means (PFCM) is one of the most widely used clustering algorithm that solves the noise sensitivity problem of Fuzzy c-means (FCM) and coincident clusters problem of possibilistic c-means (PCM). Though PFCM is a highly reliable clustering algorithm but the efficiency of the algorithm can be further improved by introducing the concept of suppression. Suppression-based algorithms employ the winner and non-winner based suppression technique on the datasets, helping in performing better classification of real-world datasets into clusters. In this paper, we propose a suppression-based possibilistic fuzzy c-means clustering algorithm (SPFCM) for the process of clustering. The paper explores the performance of the proposed methodology based on number of misclassifications for various real datasets and synthetic datasets and it is found to perform better than other clustering techniques in the sequel, i.e., normal as well as suppression-based algorithms. The SPFCM is found to perform more efficiently and converges faster as compared to other clustering techniques.
{"title":"A New Suppression-based Possibilistic Fuzzy c-means Clustering Algorithm","authors":"J. Arora, M. Tushir, Shivank Kumar Dadhwal","doi":"10.4108/eetsis.v10i3.2057","DOIUrl":"https://doi.org/10.4108/eetsis.v10i3.2057","url":null,"abstract":"Possibilistic fuzzy c-means (PFCM) is one of the most widely used clustering algorithm that solves the noise sensitivity problem of Fuzzy c-means (FCM) and coincident clusters problem of possibilistic c-means (PCM). Though PFCM is a highly reliable clustering algorithm but the efficiency of the algorithm can be further improved by introducing the concept of suppression. Suppression-based algorithms employ the winner and non-winner based suppression technique on the datasets, helping in performing better classification of real-world datasets into clusters. In this paper, we propose a suppression-based possibilistic fuzzy c-means clustering algorithm (SPFCM) for the process of clustering. The paper explores the performance of the proposed methodology based on number of misclassifications for various real datasets and synthetic datasets and it is found to perform better than other clustering techniques in the sequel, i.e., normal as well as suppression-based algorithms. The SPFCM is found to perform more efficiently and converges faster as compared to other clustering techniques.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"49 1","pages":"e3"},"PeriodicalIF":1.3,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74251834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-03DOI: 10.4108/eetsis.v10i3.2780
Bo Li, Meiqin Huang, Huanyu Zhang, Mi Lin, Shuyi He, Liming Chen
In optical fiber composite overhead ground wire (OPGW) networks, the current monitoring is mainly through installing electronic sensors on the cable and manually monitoring the video on the cable, where the interference plays an important role in the communication and monitoring based systems. In essence, the interference arises from aggressive frequency reuse, especially in the frequency-limited Internet of Things (IoT) networks. The existence of interference causes a negative effect on the system performance of communication systems and IoT networks including the OPGW networks. Hence, this article investigates the communication technology of OPGW line in distribution network under interference environment, where there is one primary link, one secondary link, and one legitimate monitor listening to the secondary link. The secondary user needs to transmit its message to the secondary receiver under the interference power constrained by the primary node. We firstly define the outage probability of legitimate monitoring based on the data rate, and then analyze the system performance by theoretically deriving a closed-form expression of the outage probability for the OPGW communication under interference environment. Simulation results are finally demonstrated to verify the correctness of the closed-form expression for the OPGW communication under interference environment, and show that the interference has a negative impact on the OPGW communication performance.
{"title":"Research on Communication Technology of OPGW Line in Distribution Network under Interference Environment","authors":"Bo Li, Meiqin Huang, Huanyu Zhang, Mi Lin, Shuyi He, Liming Chen","doi":"10.4108/eetsis.v10i3.2780","DOIUrl":"https://doi.org/10.4108/eetsis.v10i3.2780","url":null,"abstract":"In optical fiber composite overhead ground wire (OPGW) networks, the current monitoring is mainly through installing electronic sensors on the cable and manually monitoring the video on the cable, where the interference plays an important role in the communication and monitoring based systems. In essence, the interference arises from aggressive frequency reuse, especially in the frequency-limited Internet of Things (IoT) networks. The existence of interference causes a negative effect on the system performance of communication systems and IoT networks including the OPGW networks. Hence, this article investigates the communication technology of OPGW line in distribution network under interference environment, where there is one primary link, one secondary link, and one legitimate monitor listening to the secondary link. The secondary user needs to transmit its message to the secondary receiver under the interference power constrained by the primary node. We firstly define the outage probability of legitimate monitoring based on the data rate, and then analyze the system performance by theoretically deriving a closed-form expression of the outage probability for the OPGW communication under interference environment. Simulation results are finally demonstrated to verify the correctness of the closed-form expression for the OPGW communication under interference environment, and show that the interference has a negative impact on the OPGW communication performance.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"22 1","pages":"e4"},"PeriodicalIF":1.3,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89567424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-27DOI: 10.4108/eetsis.v10i3.2574
Madhu G.
INTRODUCTION: MANET is an emerging technology that has gained traction in a variety of applications due to its ability to analyze large amounts of data in a short period of time. Thus, these systems are facing a variety of security vulnerabilities and malware assaults. Therefore, it is essential to design an effective, proactive and accurate Intrusion Detection System (IDS) to mitigate these attacks present in the network. Most previous IDS faced challenges such as low detection accuracy, decreased efficiency in sensing novel forms of attacks, and a high false alarm rate. OBJECTIVES: To mitigate these concerns, the proposed model designed an efficient intrusion detection and prevention model using COOT optimization and a hybrid LSTM-KNN classifier for MANET to improve network security. METHODS: The proposed intrusion detection and prevention approach consist of four phases such as classifying normal node from attack node, predicting different types of attacks, finding the frequency of attack, and intrusion prevention mechanism. The initial phases are done through COOT optimization to find the optimal trust value for identifying attack nodes from normal nodes. In the second stage, a hybrid LSTM-KNN model is introduced for the detection of different kinds of attacks in the network. The third stage performs to classify the occurrence of attacks. RESULTS: The final stage is intended to limit the number of attack nodes present in the system. The proposed method's effectiveness is validated by some metrics, which achieved 96 per cent accuracy, 98 per cent specificity, and 35 seconds of execution time. CONCLUSION: This experimental analysis reveals that the proposed security approach effectively mitigates the malicious attack in MANET.
{"title":"Design of Intrusion Detection and Prevention Model Using COOT Optimization and Hybrid LSTM-KNN Classifier for MANET","authors":"Madhu G.","doi":"10.4108/eetsis.v10i3.2574","DOIUrl":"https://doi.org/10.4108/eetsis.v10i3.2574","url":null,"abstract":"INTRODUCTION: MANET is an emerging technology that has gained traction in a variety of applications due to its ability to analyze large amounts of data in a short period of time. Thus, these systems are facing a variety of security vulnerabilities and malware assaults. Therefore, it is essential to design an effective, proactive and accurate Intrusion Detection System (IDS) to mitigate these attacks present in the network. Most previous IDS faced challenges such as low detection accuracy, decreased efficiency in sensing novel forms of attacks, and a high false alarm rate. OBJECTIVES: To mitigate these concerns, the proposed model designed an efficient intrusion detection and prevention model using COOT optimization and a hybrid LSTM-KNN classifier for MANET to improve network security. METHODS: The proposed intrusion detection and prevention approach consist of four phases such as classifying normal node from attack node, predicting different types of attacks, finding the frequency of attack, and intrusion prevention mechanism. The initial phases are done through COOT optimization to find the optimal trust value for identifying attack nodes from normal nodes. In the second stage, a hybrid LSTM-KNN model is introduced for the detection of different kinds of attacks in the network. The third stage performs to classify the occurrence of attacks. RESULTS: The final stage is intended to limit the number of attack nodes present in the system. The proposed method's effectiveness is validated by some metrics, which achieved 96 per cent accuracy, 98 per cent specificity, and 35 seconds of execution time. CONCLUSION: This experimental analysis reveals that the proposed security approach effectively mitigates the malicious attack in MANET.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"14 1","pages":"e2"},"PeriodicalIF":1.3,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77023378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-21DOI: 10.4108/eetsis.v10i2.2948
Suha Khalil Assayed, K. Shaalan, M. Alkhatib
INTRODUCTION: An intent classification is a challenged task in Natural Language Processing (NLP) as we are asking the machine to understand our language by categorizing the users’ requests. As a result, the intent classification plays an essential role in having a chatbot conversation that understand students’ requests. OBJECTIVES: In this study, we developed a novel chatbot called “HSchatbot” for predicting the intent classifications from high school students’ enquiries. Evidently, students in high schools are the most concerned among all students about their future; thus, in this stage they need an instant support in order to prepare them to take the right decision for their career choice. METHODS: The authors in this study used the Multinomial Naive-Bayes and Random Forest classifiers for predicting the students’ enquiries, which in turn improved the performance of the classifiers by using the feature’s extractions. RESULTS: The results show that the random forest classifier performed better than Multinomial Naive-Bayes since the performance of this model is checked by using different metrics like accuracy, precision, recall and F1 score. Moreover, all showed high accuracy scores exceeding 90% in all metrics. However, the accuracy of Multinomial Naive-Bayes classifier performed much better when using CountVectorizers compared to using the TF-IDF. CONCLUSION: In the future work, the results will be analysed and investigated in order to figure out the main factors that affect the performance of Multinomial Naive-Bayes classifier, as well as evaluating the model with using a large corpus of students’ questions and enquiries.
{"title":"A Chatbot Intent Classifier for Supporting High School Students","authors":"Suha Khalil Assayed, K. Shaalan, M. Alkhatib","doi":"10.4108/eetsis.v10i2.2948","DOIUrl":"https://doi.org/10.4108/eetsis.v10i2.2948","url":null,"abstract":"INTRODUCTION: An intent classification is a challenged task in Natural Language Processing (NLP) as we are asking the machine to understand our language by categorizing the users’ requests. As a result, the intent classification plays an essential role in having a chatbot conversation that understand students’ requests. \u0000OBJECTIVES: In this study, we developed a novel chatbot called “HSchatbot” for predicting the intent classifications from high school students’ enquiries. Evidently, students in high schools are the most concerned among all students about their future; thus, in this stage they need an instant support in order to prepare them to take the right decision for their career choice. \u0000METHODS: The authors in this study used the Multinomial Naive-Bayes and Random Forest classifiers for predicting the students’ enquiries, which in turn improved the performance of the classifiers by using the feature’s extractions. \u0000RESULTS: The results show that the random forest classifier performed better than Multinomial Naive-Bayes since the performance of this model is checked by using different metrics like accuracy, precision, recall and F1 score. Moreover, all showed high accuracy scores exceeding 90% in all metrics. However, the accuracy of Multinomial Naive-Bayes classifier performed much better when using CountVectorizers compared to using the TF-IDF. \u0000CONCLUSION: In the future work, the results will be analysed and investigated in order to figure out the main factors that affect the performance of Multinomial Naive-Bayes classifier, as well as evaluating the model with using a large corpus of students’ questions and enquiries.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"86 1","pages":"e1"},"PeriodicalIF":1.3,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78707496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-23DOI: 10.4108/eetsis.v10i2.1596
Bunmi Alabi, A. David
Many businesses have been positively impacted by electronic commerce (ecommerce). It has enabled enterprises and consumers transact business digitally and experience diversity as long as the internet is accessible and there is a gadget to surf the internet. Several governments have gradually adopted electronic payment throughout the country. The Nigerian government has also done a lot of prodding toward the adoption of a cashless economy, which includes embracing ecommerce. As ecommerce expands, so does actual and attempted fraud through this channel. According to the Nigerian Central Bank, electronic fraud reached trillions of Naira by 2021. The purpose of this work was to employ logistic regression as a decision-making tool for detecting fraud in e-commerce platforms at either the virtual or physical point of sale. The main contribution of this research is a model developed using logistic regression for detecting fraud at the point of sale on electronic commerce platforms. The accuracy of the result is 97.8 percent. The result of this study will provide key decision makers in ecommerce firms with information on fraud patterns on their ecommerce platforms, this will enable them take quick actions to forestall these fraudulent attempts. Further research should be carried out using data from other developing countries.
{"title":"Framework for Detection of Fraud at Point of Sale on Electronic Commerce sites using Logistic Regression","authors":"Bunmi Alabi, A. David","doi":"10.4108/eetsis.v10i2.1596","DOIUrl":"https://doi.org/10.4108/eetsis.v10i2.1596","url":null,"abstract":"Many businesses have been positively impacted by electronic commerce (ecommerce). It has enabled enterprises and consumers transact business digitally and experience diversity as long as the internet is accessible and there is a gadget to surf the internet. Several governments have gradually adopted electronic payment throughout the country. The Nigerian government has also done a lot of prodding toward the adoption of a cashless economy, which includes embracing ecommerce. As ecommerce expands, so does actual and attempted fraud through this channel. According to the Nigerian Central Bank, electronic fraud reached trillions of Naira by 2021. The purpose of this work was to employ logistic regression as a decision-making tool for detecting fraud in e-commerce platforms at either the virtual or physical point of sale. The main contribution of this research is a model developed using logistic regression for detecting fraud at the point of sale on electronic commerce platforms. The accuracy of the result is 97.8 percent. The result of this study will provide key decision makers in ecommerce firms with information on fraud patterns on their ecommerce platforms, this will enable them take quick actions to forestall these fraudulent attempts. Further research should be carried out using data from other developing countries.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"34 1","pages":"e16"},"PeriodicalIF":1.3,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88854685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-08DOI: 10.4108/eetsis.v10i1.2575
Xinzhan Liu, Zhengfeng Zhang, Bin Du
Promoted by information technology and scalable information systems, optical fiber composite overhead ground wire (OPGW) can not only improve the use efficiency of power towers, but also give full play to the dual role of communication optical cable and ground wire, due to the advantages of high reliability, excellent mechanical performance and low cost. The effective processing of the data from OPGW can effectively promote the wide application. In this paper, we study the two-way data processing technology for OPGW line of distribution power communication networks, where a single relay node assists the two-way data processing in time-division multiplexing mode. We evaluate the influence of the model parameters on the system data processing performance by investigating the outage probability, whereas the analytical and simulation results are demonstrated to show the effectiveness of two-way data processing for the OPGW communication. The results in this paper provides important reference for the development of OPGW communication and scalable information systems.
{"title":"Two-Way Data Processing Technology for OPGW Line of Distribution Power Communication Networks","authors":"Xinzhan Liu, Zhengfeng Zhang, Bin Du","doi":"10.4108/eetsis.v10i1.2575","DOIUrl":"https://doi.org/10.4108/eetsis.v10i1.2575","url":null,"abstract":"Promoted by information technology and scalable information systems, optical fiber composite overhead ground wire (OPGW) can not only improve the use efficiency of power towers, but also give full play to the dual role of communication optical cable and ground wire, due to the advantages of high reliability, excellent mechanical performance and low cost. The effective processing of the data from OPGW can effectively promote the wide application. In this paper, we study the two-way data processing technology for OPGW line of distribution power communication networks, where a single relay node assists the two-way data processing in time-division multiplexing mode. We evaluate the influence of the model parameters on the system data processing performance by investigating the outage probability, whereas the analytical and simulation results are demonstrated to show the effectiveness of two-way data processing for the OPGW communication. The results in this paper provides important reference for the development of OPGW communication and scalable information systems.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"134 1","pages":"e15"},"PeriodicalIF":1.3,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78980921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-08DOI: 10.4108/eetsis.v10i1.2589
Shenmin Zhang, T. Gadekallu
INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output OBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is designed. METHODS: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be achieved. RESULTS: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the network. CONCLUSION: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.
{"title":"Digital interference signal filtering on laser interface for optical fiber communication","authors":"Shenmin Zhang, T. Gadekallu","doi":"10.4108/eetsis.v10i1.2589","DOIUrl":"https://doi.org/10.4108/eetsis.v10i1.2589","url":null,"abstract":"INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output\u0000OBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is designed.\u0000METHODS: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be achieved.\u0000RESULTS: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the network.\u0000CONCLUSION: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"20 1","pages":"e14"},"PeriodicalIF":1.3,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83524293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-08DOI: 10.4108/eetsis.v10i1.2527
Jiangang Lu, Zhan Shi, Xinzhan Liu
Promoted by the rapid development of information technology, 10kV overhead line has been widely used in the majority of cities, and it is of great significance to monitor the distribution network effectively, in order to ensure the normal operation of the system. Most of traditional distribution network monitoring methods are based on manual work, which causes inconvenience to the distribution network fault location, repair, maintenance and real-time monitoring, and reduces the efficiency of the distribution network emergency repair and the reliability of power supply. Aiming at the automatic monitoring problem of 10kV overhead network, this paper adopts an intelligent wireless monitoring technology, where a monitoring node is employed to monitor the network transmission status through wireless links. We evaluate the system monitoring performance by using the metric of outage probability, depending on the wireless data rate over wireless channels. For the considered system, we derive analytical outage probability, in order to measure the system performance in the whole range of signal-to-noise ratio (SNR). The simulation results are finally presented to verify the analytical expressions on the system monitoring outage probability in this paper.
{"title":"Intelligent Wireless Monitoring Technology for 10kV Overhead lines in Smart Grid Networks","authors":"Jiangang Lu, Zhan Shi, Xinzhan Liu","doi":"10.4108/eetsis.v10i1.2527","DOIUrl":"https://doi.org/10.4108/eetsis.v10i1.2527","url":null,"abstract":"Promoted by the rapid development of information technology, 10kV overhead line has been widely used in the majority of cities, and it is of great significance to monitor the distribution network effectively, in order to ensure the normal operation of the system. Most of traditional distribution network monitoring methods are based on manual work, which causes inconvenience to the distribution network fault location, repair, maintenance and real-time monitoring, and reduces the efficiency of the distribution network emergency repair and the reliability of power supply. Aiming at the automatic monitoring problem of 10kV overhead network, this paper adopts an intelligent wireless monitoring technology, where a monitoring node is employed to monitor the network transmission status through wireless links. We evaluate the system monitoring performance by using the metric of outage probability, depending on the wireless data rate over wireless channels. For the considered system, we derive analytical outage probability, in order to measure the system performance in the whole range of signal-to-noise ratio (SNR). The simulation results are finally presented to verify the analytical expressions on the system monitoring outage probability in this paper.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"44 1","pages":"e13"},"PeriodicalIF":1.3,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73206575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.4108/eetsis.v10i1.2587
Ning Zhang, Youcheng Liang, Loknath Sai Ambati
INTRODUCTION: A civil aviation security check passenger identification system based on residual convolution network is designed to improve the efficiency of airport passenger security check service. OBJECTIVES: The system uses the basic resource layer to provide communication and configuration services, collects the basic information of passengers, the images of passengers' faces and whole body, and the images of baggage security X-ray machine through the data layer, and stores the collected results in the unstructured database; METHODS: The image processing module of the business service layer calls the data in the database, and takes the STM32F103VBT6 microprocessor as the image processing control chip to complete the image data processing. The person, baggage, X-ray machine image and passenger basic information are associated through the person, baggage and X-ray machine information binding service module, and the association results are uploaded to the person and certificates integration unit of the client application layer. RESULTS: The face recognition module identifies the passenger identity through the residual convolution network with the attention mechanism, and realizes the ReID identification of passengers and baggage and the association of people and baggage through the transmission control unit. CONCLUSION: The experimental results show that the system can accurately identify the identity of civil aviation security passengers, and the identification efficiency of security passengers can reach more than 27 frames per second.
{"title":"Design of civil aviation security check passenger identification system based on residual convolution network","authors":"Ning Zhang, Youcheng Liang, Loknath Sai Ambati","doi":"10.4108/eetsis.v10i1.2587","DOIUrl":"https://doi.org/10.4108/eetsis.v10i1.2587","url":null,"abstract":"INTRODUCTION: A civil aviation security check passenger identification system based on residual convolution network is designed to improve the efficiency of airport passenger security check service.\u0000OBJECTIVES: The system uses the basic resource layer to provide communication and configuration services, collects the basic information of passengers, the images of passengers' faces and whole body, and the images of baggage security X-ray machine through the data layer, and stores the collected results in the unstructured database;\u0000METHODS: The image processing module of the business service layer calls the data in the database, and takes the STM32F103VBT6 microprocessor as the image processing control chip to complete the image data processing. The person, baggage, X-ray machine image and passenger basic information are associated through the person, baggage and X-ray machine information binding service module, and the association results are uploaded to the person and certificates integration unit of the client application layer.\u0000RESULTS: The face recognition module identifies the passenger identity through the residual convolution network with the attention mechanism, and realizes the ReID identification of passengers and baggage and the association of people and baggage through the transmission control unit.\u0000CONCLUSION: The experimental results show that the system can accurately identify the identity of civil aviation security passengers, and the identification efficiency of security passengers can reach more than 27 frames per second.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"11 1","pages":"e12"},"PeriodicalIF":1.3,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81824420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-26DOI: 10.4108/eetsis.v10i1.2578
Xu Zhu, Zhao Zhang
INTRODUCTION: With the development of the epidemic, online teaching has gradually become a hot topic. However, unlike traditional teaching programs, there are many types of physical education resources, and the recommendation of related content has always been a difficulty in online teaching. OBJECTIVES: Therefore, this paper designs an accurate recommendation algorithm for online video teaching resources of sports to meet the personalized needs of online learning of sports majors. The data layer of the entire recommendation algorithm stores the video in the database and transmits it to the service processing layer after receiving the data. METHODS: This study was conducted using techniques from social network analysis. After receiving the data, the data layer of the recommendation algorithm stores the video in the database and transmits it to the business processing layer at the same time. The business processing layer uses the designed collaborative filtering resource recommendation algorithm to formulate recommendation results for different users, and push the recommended results to the user display interface of the user layer. RESULTS: The test results of the algorithm show that the designed system has a high recommendation success rate, and the system can still maintain stable running performance when the concurrent users are 500. The average precision of resource recommendation of this method is 98.21%, the average recall rate is 98.35%, and the average F1 value is 95.37%. CONCLUSION: The proposed resource recommendation algorithm realizes accurate recommendation of sports online video teaching resources through efficient recommendation algorithms.
{"title":"Precise Recommendation Algorithm for Online Sports Video Teaching Resources","authors":"Xu Zhu, Zhao Zhang","doi":"10.4108/eetsis.v10i1.2578","DOIUrl":"https://doi.org/10.4108/eetsis.v10i1.2578","url":null,"abstract":"INTRODUCTION: With the development of the epidemic, online teaching has gradually become a hot topic. However, unlike traditional teaching programs, there are many types of physical education resources, and the recommendation of related content has always been a difficulty in online teaching. \u0000OBJECTIVES: Therefore, this paper designs an accurate recommendation algorithm for online video teaching resources of sports to meet the personalized needs of online learning of sports majors. The data layer of the entire recommendation algorithm stores the video in the database and transmits it to the service processing layer after receiving the data.\u0000METHODS: This study was conducted using techniques from social network analysis. After receiving the data, the data layer of the recommendation algorithm stores the video in the database and transmits it to the business processing layer at the same time. The business processing layer uses the designed collaborative filtering resource recommendation algorithm to formulate recommendation results for different users, and push the recommended results to the user display interface of the user layer.\u0000RESULTS: The test results of the algorithm show that the designed system has a high recommendation success rate, and the system can still maintain stable running performance when the concurrent users are 500. The average precision of resource recommendation of this method is 98.21%, the average recall rate is 98.35%, and the average F1 value is 95.37%.\u0000CONCLUSION: The proposed resource recommendation algorithm realizes accurate recommendation of sports online video teaching resources through efficient recommendation algorithms.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"25 1","pages":"e11"},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73877458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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